OBJECTIVE: To clarify the relationships of cancer pain with various factors that prevent pain control statistically. METHODS: The participants were 71 terminal cancer patients admitted to the Department of Hematology/Oncology or Department of Gastroenterology/Hepatology, University Hospital, Kyoto Prefectural University of Medicine in whose pain control a pharmacist was involved as part of her clinical duties from January 2004 to November 2006. The effectiveness of pain control was evaluated using a 5-point verbal rating scale (0=excellent, 1=good, 2=moderate, 3=poor, and 4=very poor) by interviewing the patients. As pain was rated using a graded scale and as many factors were involved in pain, analysis was performed using ordered logistic regression analysis. Moreover, prediction of an optimal model was performed by leave-one-out cross-validation to eliminate unnecessary variables. A program to perform leave-one-out cross-validation by ordered logistic regression analysis was prepared, independent variables used in the model were increased one by one, and calculation was performed in all combinations. Then, the optimal model was predicted by calculating the percent accuracy of predictions and Spearman rank correlation coefficient. RESULTS: Nausea [odds ratio (OR)=1.948, P=0.0232], sex (OR=2.322, P=0.0030), and bone metastasis (OR=2.367, P=0.0017) remained as variables significantly correlated with pain when the number of independent variables was 5, and sex (OR=2.167, P=0.006) and bone metastasis (OR=2.093, P=0.005) remained when the number of variables was 6. DISCUSSION: The statistical identification of factors preventing pain control is considered to contribute to the establishment of an evidence-based approach to cancer pain relief.
OBJECTIVE: To clarify the relationships of cancer pain with various factors that prevent pain control statistically. METHODS: The participants were 71 terminal cancerpatients admitted to the Department of Hematology/Oncology or Department of Gastroenterology/Hepatology, University Hospital, Kyoto Prefectural University of Medicine in whose pain control a pharmacist was involved as part of her clinical duties from January 2004 to November 2006. The effectiveness of pain control was evaluated using a 5-point verbal rating scale (0=excellent, 1=good, 2=moderate, 3=poor, and 4=very poor) by interviewing the patients. As pain was rated using a graded scale and as many factors were involved in pain, analysis was performed using ordered logistic regression analysis. Moreover, prediction of an optimal model was performed by leave-one-out cross-validation to eliminate unnecessary variables. A program to perform leave-one-out cross-validation by ordered logistic regression analysis was prepared, independent variables used in the model were increased one by one, and calculation was performed in all combinations. Then, the optimal model was predicted by calculating the percent accuracy of predictions and Spearman rank correlation coefficient. RESULTS:Nausea [odds ratio (OR)=1.948, P=0.0232], sex (OR=2.322, P=0.0030), and bone metastasis (OR=2.367, P=0.0017) remained as variables significantly correlated with pain when the number of independent variables was 5, and sex (OR=2.167, P=0.006) and bone metastasis (OR=2.093, P=0.005) remained when the number of variables was 6. DISCUSSION: The statistical identification of factors preventing pain control is considered to contribute to the establishment of an evidence-based approach to cancer pain relief.